Optimizing Juvenile Assessment Performance, United States, 2003-2019 (ICPSR 37840)

Version Date: Mar 25, 2021 View help for published

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Zachary Hamilton, Washington State University at Spokane

https://doi.org/10.3886/ICPSR37840.v1

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In nearly every state and in the vast majority of juvenile justice agencies, risk assessments are incorporated into diversion, case management, supervision, and placement practices. Despite two decades of use within the juvenile justice system, little research regarding the methods of risk assessment development is discussed or translated to the field and practitioners. Many of the contemporary tools used today are implemented off-the-shelf, meaning that tools were developed with a specific set of methods, selecting and weighting items used in the prediction of a specified sample of youth. What is not known is how the various designs, methods, and circumstances of tool development impact the predictive performance when adopted by a jurisdiction. This study seeks to provide input into this dilemma. Demographic information in this study includes age, race, and sex.

Hamilton, Zachary. Optimizing Juvenile Assessment Performance, United States, 2003-2019. Inter-university Consortium for Political and Social Research [distributor], 2021-03-25. https://doi.org/10.3886/ICPSR37840.v1

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United States Department of Justice. Office of Justice Programs. Office of Juvenile Justice and Delinquency Prevention (2017-JF-FX-0063)

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Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reasons for the request, and obtain IRB approval or notice of exemption for their research.

Inter-university Consortium for Political and Social Research
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2003 -- 2019 (Master Dataset), 2011 -- 2016 (Eastern 1 Dataset), 2009 -- 2018 (Eastern 2 Dataset), 2012 -- 2016 (Southeastern Dataset), 2009 -- 2015 (Southern 1 Dataset), 2006 -- 2017 (Southern 2 Dataset), 2008 -- 2015 (Midwestern Dataset), 2008 -- 2017 (Mountain 1 Dataset), 2010 -- 2017 (Mountain 2 Dataset), 2003 -- 2018 (Western 1 Dataset), 2005 -- 2016 (Western 2 Dataset)
2003 -- 2019
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The study sought to isolate, test, and evaluate the relative impact of seven notable risk assessment development variations, namely:

  1. Item selection technique,
  2. Weighting,
  3. Gender-specificity,
  4. Race-ethnicity neutrality,
  5. Outcome specificity,
  6. Prediction duration, and
  7. Jurisdiction variation.

It was anticipated that each tested variation would provide a small-to-substantial impact on the predictive performance of assessments evaluated.

Using a large, aggregated, multi-state sample of youth assessed using the same risk-needs assessment item pool, the study created risk assessments using the seven development methods outlined. Item clusters, or factors, were also identified, for potential use as scales in the modeling process. Where required, boosted regression models were used for identifying predictive items and providing coefficient weights. In addition, several sub-samples were created to examine and compare approaches between gender and race/ethnic groupings. Furthermore, comparisons were made between the 10-site unified sample and models created to capture individual site differences. To identify model performance, M-fold validation was completed, where industry standard Area Under the Curve (AUC) statistics are provided.

Data gathered in 10 states by risk assessment tools based on the Washington State Juvenile Court Authority - Risk Assessment (WSJCA-RA).

Cross-sectional

Risk assessment tools used by juvenile justice agencies.

Individual

The variables in this study are divided into the following categories:

  • Recidivism measures
  • Criminal history
  • School status
  • Use of free time
  • Employment status
  • Status of relationships
  • Family history
  • Living arrangements
  • Alcohol and drug use
  • Mental health status
  • Attitudes/behaviors
  • Aggression
  • Skills

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2021-03-25

2021-03-25 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Created variable labels and/or value labels.
  • Checked for undocumented or out-of-range codes.

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Notes

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.

  • ICPSR usually offers files in multiple formats for researchers to be able to access data and documentation in formats that work well within their needs. If you have questions about the accessibility of materials distributed by ICPSR or require further assistance, please visit ICPSR’s Accessibility Center.

  • One or more files in this data collection have special restrictions. Restricted data files are not available for direct download from the website; click on the Restricted Data button to learn more.

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This dataset is maintained and distributed by the National Archive of Criminal Justice Data (NACJD), the criminal justice archive within ICPSR. NACJD is primarily sponsored by three agencies within the U.S. Department of Justice: the Bureau of Justice Statistics, the National Institute of Justice, and the Office of Juvenile Justice and Delinquency Prevention.